Browse publications by year: 2024

  1. Ahmed KI, Tahir M, Lau SL, Habaebi MH, Ahad A, Pires IM
    Data Brief, 2024 Aug;55:110589.
    PMID: 39022696 DOI: 10.1016/j.dib.2024.110589
    The proliferation landscape of the Internet of Things (IoT) has accentuated the critical role of Authentication and Authorization (AA) mechanisms in securing interconnected devices. There is a lack of relevant datasets that can aid in building appropriate machine learning enabled security solutions focusing on authentication and authorization using physical layer characteristics. In this context, our research presents a novel dataset derived from real-world scenarios, utilizing Zigbee Zolertia Z1 nodes to capture physical layer properties in indoor environments. The dataset encompasses crucial parameters such as Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), Device Internal Temperature, Device Battery Level, and more, providing a comprehensive foundation for advancing Machine learning enabled AA in IoT ecosystems.
  2. Siti Athirah B, Mohd Hafiz S, Dong LN, Lim PS, Nasrinsa SH, Nor Aliah MN, et al.
    PMID: 39022789 DOI: 10.51866/oa.487
    INTRODUCTION: Family planning (FP) is important in reducing maternal morbidity and mortality as well as foetal and neonatal complications. This study aimed to determine the intention to practise FP among antenatal women at risk of gestational diabetes mellitus (GDM) in the Klang Health District and its associated factors.

    METHODS: A cross-sectional study was conducted at four government health clinics in the Klang Health District. A total of 431 antenatal women at risk of GDM were recruited using systematic random sampling. A validated self-administered questionnaire was used to assess knowledge, attitude, previous practice and intention to use FP after delivery. Multiple logistic regression (MLR) was used to determine the factors associated with the intention to practise FP.

    RESULTS: Approximately 64.7% (n=279) of the respondents intended to practise FP MLR showed that the factors associated with the intention to practise FP were Malay ethnicity (odds ratio [OR]=3.319, 95% confidence interval [CI]=1.431-7.697), low income (OR=2.174, 95% CI=1.317-3.588), good knowledge (OR=2.591, 95% CI=L008-6.174) and good previous practice (OR=3.956, 95% CI=1.428-9.052).

    CONCLUSION: The prevalence of the intention to practise FP among antenatal women at risk of GDM was 64.7%. Malay antenatal women from low-income households with good knowledge and previous practice were more likely to have the intention to practise FP after delivery. Thus, interventions targeted at non-Malay women and measures to improve their knowledge might help improve the intention and uptake of FP among these women.

  3. Chen J, Kaya NA, Zhang Y, Kendarsari RI, Sekar K, Lee Chong S, et al.
    J Hepatol, 2024 May 21.
    PMID: 38782118 DOI: 10.1016/j.jhep.2024.05.017
    BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a highly fatal cancer characterized by high intra-tumor heterogeneity (ITH). A panoramic understanding of its tumor evolution, in relation to its clinical trajectory, may provide novel prognostic and treatment strategies.

    METHODS: Through the Asia-Pacific Hepatocellular Carcinoma trials group (NCT03267641), we recruited one of the largest prospective cohorts of patients with HCC, with over 600 whole genome and transcriptome samples from 123 treatment-naïve patients.

    RESULTS: Using a multi-region sampling approach, we revealed seven convergent genetic evolutionary paths governed by the early driver mutations, late copy number variations and viral integrations, which stratify patient clinical trajectories after surgical resection. Furthermore, such evolutionary paths shaped the molecular profiles, leading to distinct transcriptomic subtypes. Most significantly, although we found the coexistence of multiple transcriptomic subtypes within certain tumors, patient prognosis was best predicted by the most aggressive cell fraction of the tumor, rather than by overall degree of transcriptomic ITH level - a phenomenon we termed the 'bad apple' effect. Finally, we found that characteristics throughout early and late tumor evolution provide significant and complementary prognostic power in predicting patient survival.

    CONCLUSIONS: Taken together, our study generated a comprehensive landscape of evolutionary history for HCC and provides a rich multi-omics resource for understanding tumor heterogeneity and clinical trajectories.

    IMPACT AND IMPLICATIONS: This prospective study, utilizing comprehensive multi-sector, multi-omics sequencing and clinical data from surgically resected hepatocellular carcinoma (HCC), reveals critical insights into the role of tumor evolution and intra-tumor heterogeneity (ITH) in determining the prognosis of HCC. These findings are invaluable for oncology researchers and clinicians, as they underscore the influence of distinct evolutionary paths and the 'bad apple' effect, where the most aggressive tumor fraction dictates disease progression. These insights not only enhance prognostic accuracy post-surgical resection but also pave the way for personalized treatment strategies tailored to specific tumor evolutionary and transcriptomic profiles. The coexistence of multiple subtypes within the same tumor prompts a re-appraisal of the utilities of depending on single samples to represent the entire tumor and suggests the need for clinical molecular imaging. This research thus marks a significant step forward in the clinical understanding and management of HCC, underscoring the importance of integrating tumor evolutionary dynamics and multi-omics biomarkers into therapeutic decision-making.

    CLINICAL TRIAL NUMBER: NCT03267641 (Observational cohort).

  4. Jain L, Pradhan S, Aggarwal A, Padhi BK, Itumalla R, Khatib MN, et al.
    JMIR Public Health Surveill, 2024 May 24;10:e41567.
    PMID: 38787607 DOI: 10.2196/41567
    BACKGROUND: Undernutrition among children younger than 5 years is a subtle indicator of a country's health and economic status. Despite substantial macroeconomic progress in India, undernutrition remains a significant burden with geographical variations, compounded by poor access to water, sanitation, and hygiene services.

    OBJECTIVE: This study aimed to explore the spatial trends of child growth failure (CGF) indicators and their association with household sanitation practices in India.

    METHODS: We used data from the Indian Demographic and Health Surveys spanning 1998-2021. District-level CGF indicators (stunting, wasting, and underweight) were cross-referenced with sanitation and sociodemographic characteristics. Global Moran I and Local Indicator of Spatial Association were used to detect spatial clustering of the indicators. Spatial regression models were used to evaluate the significant determinants of CGF indicators.

    RESULTS: Our study showed a decreasing trend in stunting (44.9%-38.4%) and underweight (46.7%-35.7%) but an increasing prevalence of wasting (15.7%-21.0%) over 15 years. The positive values of Moran I between 1998 and 2021 indicate the presence of spatial autocorrelation. Geographic clustering was consistently observed in the states of Madhya Pradesh, Jharkhand, Odisha, Uttar Pradesh, Chhattisgarh, West Bengal, Rajasthan, Bihar, and Gujarat. Improved sanitation facilities, a higher wealth index, and advanced maternal education status showed a significant association in reducing stunting. Relative risk maps identified hotspots of CGF health outcomes, which could be targeted for future interventions.

    CONCLUSIONS: Despite numerous policies and programs, malnutrition remains a concern. Its multifaceted causes demand coordinated and sustained interventions that go above and beyond the usual. Identifying hotspot locations will aid in developing control methods for achieving objectives in target areas.

    MeSH terms: Child, Preschool; Family Characteristics; Female; Growth Disorders/epidemiology; Health Surveys; Humans; India/epidemiology; Infant; Male; Child Nutrition Disorders/epidemiology; Spatio-Temporal Analysis
  5. Boidin L, Moinard M, Moussaron A, Merlier M, Moralès O, Grolez GP, et al.
    J Control Release, 2024 Jul;371:351-370.
    PMID: 38789088 DOI: 10.1016/j.jconrel.2024.05.033
    Ovarian cancer (OC) is one of the most lethal cancers among women. Frequent recurrence in the peritoneum due to the presence of microscopic tumor residues justifies the development of new therapies. Indeed, our main objective is to develop a targeted photodynamic therapy (PDT) treatment of peritoneal carcinomatosis from OC to improve the life expectancy of cancer patients. Herein, we propose a targeted-PDT using a vectorized photosensitizer (PS) coupled with a newly folic acid analog (FAA), named PSFAA, in order to target folate receptor alpha (FRα) overexpressed on peritoneal metastasis. This PSFAA was the result of the coupling of pyropheophorbide-a (Pyro-a), as the PS, to a newly synthesized FAA via a polyethylene glycol (PEG) spacer. The selectivity and the PDT efficacy of PSFAA was evaluated on two human OC cell lines overexpressing FRα compared to fibrosarcoma cells underexpressing FRα. Final PSFAA, including the synthesis of a newly FAA and its conjugation to Pyro-a, was obtained after 10 synthesis steps, with an overall yield of 19%. Photophysical properties of PSFAA in EtOH were performed and showed similarity with those of free Pyro-a, such as the fluorescence and singlet oxygen quantum yields (Φf = 0.39 and ΦΔ = 0.53 for free Pyro-a, and Φf = 0.26 and ΦΔ = 0.41 for PSFAA). Any toxicity of PSFAA was noticed. After light illumination, a dose-dependent effect on PS concentration and light dose was shown. Furthermore, a PDT efficacy of PSFAA on OC cell secretome was detected inducing a decrease of a pro-inflammatory cytokine secretion (IL-6). This new PSFAA has shown promising biological properties highlighting the selectivity of the therapy opening new perspectives in the treatment of a cancer in a therapeutic impasse.
    MeSH terms: Cell Survival/drug effects; Female; Humans; Inflammation/drug therapy; Cell Death/drug effects; Cell Line, Tumor; Folate Receptor 1/metabolism
  6. Abdullah MA, Chuah LF, Abdullah SB, Bokhari A, Syed A, Elgorban AM, et al.
    Environ Res, 2024 Sep 15;257:119328.
    PMID: 38851369 DOI: 10.1016/j.envres.2024.119328
    The growing effects of climate change on Malaysia's coastal ecology heighten worries about air pollution, specifically caused by urbanization and industrial activity in the maritime sector. Trucks and vessels are particularly noteworthy for their substantial contribution to gas emissions, including nitrogen dioxide (NO2), which is the primary gas released in port areas. The application of advanced analysis techniques was spurred by the air pollution resulting from the combustion of fossil fuels such as fuel oil, natural gas and gasoline in vessels. The study utilized satellite photos captured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5P satellite to evaluate the levels of NO2 gas pollution in Malaysia's port areas and exclusive economic zone. Before the COVID-19 pandemic, unrestricted gas emissions led to persistently high levels of NO2 in the analyzed areas. The temporary cessation of marine industry operations caused by the pandemic, along with the halting of vessels to prevent the spread of COVID-19, resulted in a noticeable decrease in NO2 gas pollution. In light of these favourable advancements, it is imperative to emphasize the need for continuous investigation and collaborative endeavours to further alleviate air contamination in Malaysian port regions, while simultaneously acknowledging the wider consequences of climate change on the coastal ecology. The study underscores the interdependence of air pollution, maritime activities and climate change. It emphasizes the need for comprehensive strategies that tackle both immediate environmental issues and the long-term sustainability and resilience of coastal ecosystems in the context of global climate challenges.
    MeSH terms: Vehicle Emissions/analysis; Malaysia; Ships; Climate Change*; Satellite Imagery*
  7. Jagaba AH, Lawal DU, Yassin MA, Abdulazeez I, Mu'azu ND, Usman AK, et al.
    Environ Res, 2024 Sep 15;257:119381.
    PMID: 38857858 DOI: 10.1016/j.envres.2024.119381
    This study assessed the efficacy of granular cylindrical periodic discontinuous batch reactors (GC-PDBRs) for produced water (PW) treatment by employing eggshell and waste activated sludge (WAS) derived Nickel (Ni) augmented biochar. The synthesized biochar was magnetized to further enhance its contribution towards achieving carbon neutrality due to carbon negative nature, Carbon dioxide (CO2) sorption, and negative priming effects. The GC-PDBR1 and GC-PDBR2 process variables were optimized by the application of central composite design (CCD). This is to maximize the decarbonization rate. Results showed that the systems could reduce total phosphorus (TP) and chemical oxygen demand (COD) by 76-80% and 92-99%, respectively. Optimal organic matter and nutrient removals were achieved at 80% volumetric exchange ratio (VER), 5 min settling time and 3000 mg/L mixed liquor suspended solids (MLSS) concentration with desirability values of 0.811 and 0.954 for GC-PDBR1 and GC-PDBR2, respectively. Employing four distinct models, the biokinetic coefficients of the GC-PDBRs treating PW were calculated. The findings indicated that First order (0.0758-0.5365) and Monod models (0.8652-0.9925) have relatively low R2 values. However, the Grau Second-order model and Modified Stover-Kincannon model have high R2 values. This shows that, the Grau Second Order and Modified Stover-Kincannon models under various VER, settling time, and MLSS circumstances, are more suited to explain the removal of pollutants in the GC-PDBRs. Microbiological evaluation demonstrated that a high VER caused notable rises in the quantity of several microorganisms. Under high biological selective pressure, GC-PDBR2 demonstrated a greater percentage of nitrogen removal via autotrophic denitrification and a greater number of nitrifying bacteria. The overgrowth of bacteria such as Actinobacteriota spp. Bacteroidota spp, Gammaproteobacteria, Desulfuromonas Mesotoga in the phylum, class, and genus, has positively impacted on granule formation and stability. Taken together, our study through the introduction of intermittent aeration GC-PDBR systems with added magnetized waste derived biochar, is an innovative approach for simultaneous aerobic sludge granulation and PW treatment, thereby providing valuable contributions in the journey toward achieving decarbonization, carbon neutrality and sustainable development goals (SDGs).
    MeSH terms: Oil and Gas Industry; Aerobiosis; Anaerobiosis; Industrial Waste/analysis; Nickel*; Waste Disposal, Fluid/methods; Water Pollutants, Chemical/analysis; Water Purification/methods; Bioreactors*
  8. Zambry NS, Awang MS, Hamzah HH, Mohamad AN, Khalid MF, Khim BK, et al.
    Anal Methods, 2024 Jul 16.
    PMID: 39011785 DOI: 10.1039/d4ay00888j
    A highly accurate, rapid, portable, and robust platform for detecting Salmonella enterica serovar Typhi (S. Typhi) is crucial for early-stage diagnosis of typhoid to avert and control the outbreaks of this pathogen, which threaten global public health. This study presents a proof-of-concept for our developed label-free electrochemical DNA biosensor system for S. Typhi detection, which employs a printed circuit board gold electrode (PCBGE), integrated with a portable potentiostat reader. Initially, the functionalized DNA biosensor and target detection were characterized using cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS) methods using a benchtop potentiostat. Interestingly, the newly developed DNA biosensor can identify target single-stranded DNA concentrations ranging from 10 nM to 20 μM, achieving a detection limit of 7.6 nM within a brief 5 minute timeframe. Under optimal detection conditions, the DNA biosensor exhibits remarkable selectivity, capable of distinguishing a single mismatch base pair from the target single-stranded DNA sequence. We then evaluated the feasibility of the developed DNA biosensor system as a diagnostic tool by detecting S. Typhi in 50 clinical samples using a portable potentiostat reader based on the DPV technique. Remarkably, the developed biosensor can distinctly distinguish between positive and negative samples, indicating that the miniaturised DNA biosensor system is practical for detecting S. Typhi in real biological samples. The developed DNA biosensor device in this work proves to be a promising point-of-care (POC) device for Salmonella detection due to its swift detection time, uncomplicated design, and streamlined workflow detection system.
  9. Gan HM, Liew LY, Savka MA
    Microbiol Resour Announc, 2024 Aug 13;13(8):e0046824.
    PMID: 39012133 DOI: 10.1128/mra.00468-24
    Using Nanopore Q20+ sequencing, we report the complete genome of Allorhizobium (Agrobacterium) vitis strain CG957=AA25, isolated nearly 40 years ago from a grapevine crown gall in Afghanistan. The assembled genome size is 6 Mb, comprising a circular chromosome, a linear chromid, a Ti plasmid, and two non-Ti plasmids.
  10. Foo JJ, Ng SF, Xiong M, Ong WJ
    Nanoscale, 2024 Jul 16.
    PMID: 39012281 DOI: 10.1039/d4nr01932f
    In the context of catalytic CO2 reduction (CO2RR), the interference of the inherent hydrogen evolution reaction (HER) and the possible selectivity towards CO have posed a significant challenge to the generation of formic acid. To address this hurdle, in this work, we have investigated the impact of different single-atom metal catalysts on tuning selectivity by employing density functional theory (DFT) calculations to scrutinize the reaction pathways. Single-atom catalysts supported on carbon-based systems have proven to be pivotal in altering both the activity and selectivity of the CO2RR. In this study, a series of single-atom-metal-loaded g-C3N4 monolayers (MCN, M = Ni, Cu, Zn, Ga, Cd, In, Sn, Pb, Ag, Au, Bi, Pd and Pt) were systematically examined. Through detailed DFT calculations, we explored their influence on reaction selectivity between the *COOH and *OCHO intermediates. Notably, NiCN favors the reaction via the *OCHO route, with a significantly lower rate-determining potential of 0.36 eV, which is approximately 73.5% lower than that of the CN system (1.36 eV). Most importantly, the Ni single-atom catalyst with lower coordination significantly enhances CO2 adsorption, promoting CO2RR over HER. Overall, this study, guided by DFT calculations, provides a theoretical prediction of how the selection of single-atom metal catalysts can effectively modulate the reaction pathway, thereby offering a potential solution for achieving high product selectivity in CO2RR.
  11. Lin Y, Xu X, Liu Y, Alias H, Hu Z, Wong LP
    J Med Internet Res, 2024 Jul 16;26:e53497.
    PMID: 39012687 DOI: 10.2196/53497
    BACKGROUND: The COVID-19 pandemic is bringing about substantial changes in health care systems, leading to a significant shift toward telemedicine for the delivery of health care services.

    OBJECTIVE: This study aims to examine the relationship between perceived usefulness and ease of use of telemedicine services and their association with the behavioral intention to use telemedicine.

    METHODS: An anonymous cross-sectional survey was conducted in China. Partial least squares structural equation modeling was used to determine significant predictors of intention to use telemedicine consultation. Types of illnesses that favored seeking telemedicine consultation, as well as the most preferred platform for conducting telemedicine consultations, were also investigated.

    RESULTS: In total, 1006 participants completed the survey. A total of 44.3% (n=446) reported being very likely and 49.3% (n=496) reported being likely to seek telemedicine consultation. Overall, the majority of participants expressed strong agreement or agreement regarding the perceived usefulness of telemedicine. Likewise, the majority indicated strong agreement or agreement when it came to their perception of the ease of using telemedicine. In the partial least squares structural equation modeling, perceived usefulness (β=0.322; P

    MeSH terms: Adolescent; Adult; China; Cross-Sectional Studies; Female; Humans; Male; Middle Aged; Surveys and Questionnaires; Young Adult; Pandemics
  12. Anisha SA, Sen A, Bain C
    J Med Internet Res, 2024 Jul 16;26:e56114.
    PMID: 39012688 DOI: 10.2196/56114
    BACKGROUND: The rising prevalence of noncommunicable diseases (NCDs) worldwide and the high recent mortality rates (74.4%) associated with them, especially in low- and middle-income countries, is causing a substantial global burden of disease, necessitating innovative and sustainable long-term care solutions.

    OBJECTIVE: This scoping review aims to investigate the impact of artificial intelligence (AI)-based conversational agents (CAs)-including chatbots, voicebots, and anthropomorphic digital avatars-as human-like health caregivers in the remote management of NCDs as well as identify critical areas for future research and provide insights into how these technologies might be used effectively in health care to personalize NCD management strategies.

    METHODS: A broad literature search was conducted in July 2023 in 6 electronic databases-Ovid MEDLINE, Embase, PsycINFO, PubMed, CINAHL, and Web of Science-using the search terms "conversational agents," "artificial intelligence," and "noncommunicable diseases," including their associated synonyms. We also manually searched gray literature using sources such as ProQuest Central, ResearchGate, ACM Digital Library, and Google Scholar. We included empirical studies published in English from January 2010 to July 2023 focusing solely on health care-oriented applications of CAs used for remote management of NCDs. The narrative synthesis approach was used to collate and summarize the relevant information extracted from the included studies.

    RESULTS: The literature search yielded a total of 43 studies that matched the inclusion criteria. Our review unveiled four significant findings: (1) higher user acceptance and compliance with anthropomorphic and avatar-based CAs for remote care; (2) an existing gap in the development of personalized, empathetic, and contextually aware CAs for effective emotional and social interaction with users, along with limited consideration of ethical concerns such as data privacy and patient safety; (3) inadequate evidence of the efficacy of CAs in NCD self-management despite a moderate to high level of optimism among health care professionals regarding CAs' potential in remote health care; and (4) CAs primarily being used for supporting nonpharmacological interventions such as behavioral or lifestyle modifications and patient education for the self-management of NCDs.

    CONCLUSIONS: This review makes a unique contribution to the field by not only providing a quantifiable impact analysis but also identifying the areas requiring imminent scholarly attention for the ethical, empathetic, and efficacious implementation of AI in NCD care. This serves as an academic cornerstone for future research in AI-assisted health care for NCD management.

    TRIAL REGISTRATION: Open Science Framework; https://doi.org/10.17605/OSF.IO/GU5PX.

    MeSH terms: Artificial Intelligence*; Humans; Telemedicine*
  13. Poddar A, Satthiyasilan N, Wang PH, Chen C, Yi R, Chandru K, et al.
    Acc Chem Res, 2024 Aug 06;57(15):2048-2057.
    PMID: 39013010 DOI: 10.1021/acs.accounts.4c00167
    All life on Earth is composed of cells, which are built from and run by biological reactions and structures. These reactions and structures are generally the result of action by cellular biomolecules, which are indispensable for the function and survival of all living organisms. Specifically, biological catalysis, namely by protein enzymes, but also by other biomolecules including nucleic acids, is an essential component of life. How the biomolecules themselves that perform biological catalysis came to exist in the first place is a major unanswered question that plagues researchers to this day, which is generally the focus of the origins of life (OoL) research field. Based on current knowledge, it is generally postulated that early Earth was full of a myriad of different chemicals, and that these chemicals reacted in specific ways that led to the emergence of biochemistry, cells, and later, life. In particular, a significant part of OoL research focuses on the synthesis, evolution, and function of biomolecules potentially present under early Earth conditions, as a way to understand their eventual transition into modern life. However, this narrative overlooks possibilities that other molecules contributed to the OoL, as while biomolecules that led to life were certainly present on early Earth, at the same time, other molecules that may not have strict, direct biological lineage were also widely and abundantly present. For example, hydroxy acids, although playing a role in metabolism or as parts of certain biological structures, are not generally considered to be as essential to modern biology as amino acids (a chemically similar monomer), and thus research in the OoL field tends to perhaps focus more on amino acids than hydroxy acids. However, their likely abundance on early Earth coupled with their ability to spontaneously condense into polymers (i.e., polyesters) make hydroxy acids, and their subsequent products, functions, and reactions, a reasonable target of investigation for prebiotic chemists. Whether "non-biological" hydroxy acids or polyesters can contribute to the emergence of life on early Earth is an inquiry that deserves attention within the OoL community, as this knowledge can also contribute to our understanding of the plausibility of extraterrestrial life that does not exactly use the biochemical set found in terrestrial organisms. While some demonstrations have been made with respect to compartment assembly, compartmentalization, and growth of primitive polyester-based systems, whether these "non-biological" polymers can contribute any catalytic function and/or drive primitive reactions is still an important step toward the development of early life. Here, we review research both from the OoL field as well as from industry and applied sciences regarding potential catalysis or reaction driven by "non-biological" polyesters in various forms: as linear polymers, as hyperbranched polyesters, and as membraneless microdroplets.
    MeSH terms: Origin of Life*
  14. Cárdenas H, Kamrul-Bahrin MAH, Seddon D, Othman J, Cabral JT, Mejía A, et al.
    J Colloid Interface Sci, 2024 Jul 08;674:1071-1082.
    PMID: 39013277 DOI: 10.1016/j.jcis.2024.07.002
    Hypothesis Atomistically-detailed models of surfactants provide quantitative information on the molecular interactions and spatial distributions at fluid interfaces. Hence, it should be possible to extract from this information, macroscopical thermophysical properties such as interfacial tension, critical micelle concentrations and the relationship between these properties and the bulk fluid surfactant concentrations. Simulations and Experiments Molecular-scale interfacial of systems containing n-dodecyl β-glucoside (APG12) are simulated using classical molecular dynamics. The bulk phases and the corresponding interfacial regions are all explicitly detailed using an all-atom force field (PCFF+). During the simulation, the behaviour of the interface is analyzed geometrically to obtain an approximated value of the critical micelle concentration (CMC) in terms of the surfactant area number density and the interfacial tension is assessed through the analysis of the forces amongst molecules. New experimental determinations are reported for the surface tension of APG12 at the water/air and at the water/n-decane interfaces. Findings We showcase the application of a thermodynamic framework that inter-relates interfacial tensions, surface densities, CMCs and bulk surfactant concentrations, which allows the in silico quantitative prediction of interfacial tension isotherms.
  15. Tian C, Di L, Dong S, Tian X, Huang D, Zhao Y, et al.
    Infect Genet Evol, 2024 Sep;123:105642.
    PMID: 39013496 DOI: 10.1016/j.meegid.2024.105642
    Nosocomial outbreaks caused by carbapenem-resistant Acinetobacter baumannii (CRAB) strains are rapidly emerging worldwide and are cause for concern. Herein, we aimed to describe the genomic characteristics of CRAB strains isolated from two hospitals in China in 2023. The A. baumannii isolates were mainly collected from the ICU and isolated from the sputum (71.43%, 15/21), followed by urine (14.29%, 3/21). Twenty-one A. baumannii strains possessed a multidrug-resistant (MDR) profile, and whole-genome sequencing showed that they all carried blaOXA-23. Based on the Pasteur multilocus sequence typing (MLST) scheme, all strains were typed into a sequence type 2 (ST2). Based on the Oxford MLST scheme, six strains belonged to ST540, three of which were ST208, and four strains were assigned to ST784. Kaptive showed most of the strains (38.10%, 8/21) contained KL93. As for the lipoolygosaccharide (OC locus) type, OCL1c and OCL1d were identified, accounting for 33.33% (7/21) and 66.67% (14/21), respectively. Based on the BacWGSTdb server, we found that the strains belonging to ST540 and ST784 were all collected from China. However, the ST938 strains were isolated from Malaysia and Thailand. Comparative genomics analysis showed that the AB10 strain had a closed relationship with SXAB10-SXAB13 strains, suggesting the transmission happened in these two hospitals and other hospital in China. In addition, the 4300STDY7045869 strain, which was collected from Thailand, possessed near genetic relationship with our isolates in this study, suggesting the possible spread among various countries. Additionally, 3-237 single nucleotide polymorphisms were observed among these strains. In conclusion, this study conducted a genome-based study for A. baumannii strains collected from two hospitals in China and revealed their epidemiological and molecular features. Clone spreading occurred in these two hospitals. Hence, there is an urgent need for increased surveillance in hospitals and other clinical settings to prevent and control CRAB spreading.
    MeSH terms: beta-Lactamases/genetics; China/epidemiology; Cross Infection/microbiology; Cross Infection/epidemiology; Hospitals; Humans; Microbial Sensitivity Tests; Phylogeny; Genome, Bacterial; Drug Resistance, Multiple, Bacterial/genetics; Multilocus Sequence Typing*
  16. Mesinovic M, Wong XC, Rajahram GS, Citarella BW, Peariasamy KM, van Someren Greve F, et al.
    Sci Rep, 2024 Jul 16;14(1):16387.
    PMID: 39013928 DOI: 10.1038/s41598-024-63212-7
    By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients.
    MeSH terms: Machine Learning*; Adult; Aged; Aged, 80 and over; Female; Great Britain/epidemiology; Hospitalization; Humans; Male; Middle Aged; Risk Factors; Spain/epidemiology; Cohort Studies
  17. Chai CS, Bin Ibrahim MA, Binti Azhar NA, Binti Roslan Z, Binti Harun R, Krishnabahawan SL, et al.
    Sci Rep, 2024 Jul 16;14(1):16413.
    PMID: 39013943 DOI: 10.1038/s41598-024-67536-2
    Understanding the prevalence of abnormal lung function and its associated factors among patients recovering from COVID-19 is crucial for enhancing post-COVID care strategies. This study primarily aimed to determine the prevalence and types of spirometry abnormalities among post-COVID-19 patients in Malaysia, with a secondary objective of identifying its associated factors. Conducted at the COVID-19 Research Clinic, Faculty of Medicine, University Technology MARA, from March 2021 to December 2022, this study included patients at least three months post-discharge from hospitals following moderate-to-critical COVID-19. Of 408 patients studied, abnormal spirometry was found in 46.8%, with 28.4% exhibiting a restrictive pattern, 17.4% showing preserved ratio impaired spirometry (PRISm), and 1.0% displaying an obstructive pattern. Factors independently associated with abnormal spirometry included consolidation on chest X-ray (OR 8.1, 95% CI 1.75-37.42, p = 0.008), underlying cardiovascular disease (OR 3.5, 95% CI 1.19-10.47, p = 0.023), ground-glass opacity on chest X-ray (OR 2.6, 95% CI 1.52-4.30, p 
    MeSH terms: Adult; Aged; Cross-Sectional Studies; Female; Humans; Lung/physiopathology; Malaysia/epidemiology; Male; Middle Aged; Patient Discharge*; Prevalence
  18. Musa M, Rahman P, Saha SK, Chen Z, Ali MAS, Gao Y
    Sci Rep, 2024 Jul 16;14(1):16357.
    PMID: 39014028 DOI: 10.1038/s41598-024-67199-z
    Within the intricate interplay of socio-economic, natural and anthropogenic factors, haze pollution stands as a stark emblem of environmental degradation, particularly in the South Asian Association for Regional Cooperation (SAARC) region. Despite significant efforts to mitigate greenhouse gas emissions, several SAARC nations consistently rank among the world's most polluted. Addressing this critical research gap, this study employs robust econometric methodologies to elucidate the dynamics of haze pollution across SAARC countries from 1998 to 2020. These methodologies include the Pooled Mean Group (PMG) and Augmented Mean Group (AMG) estimator, Panel two-stage least squares (TSLS), Feasible Generalized Least Squares (FGLS) and Dumitrescu-Hurlin (D-H) causality test. The analysis reveals a statistically significant cointegrating relationship between PM2.5 and economic indicators, with economic development and consumption expenditure exhibiting positive associations and rainfall demonstrating a mitigating effect. Furthermore, a bidirectional causality is established between temperature and economic growth, both influencing PM2.5 concentrations. These findings emphasize the crucial role of evidence-based policy strategies in curbing air pollution. Based on these insights, recommendations focus on prioritizing green economic paradigms, intensifying forest conservation efforts, fostering the adoption of eco-friendly energy technologies in manufacturing and proactively implementing climate-sensitive policies. By embracing these recommendations, SAARC nations can formulate comprehensive and sustainable approaches to combat air pollution, paving the way for a healthier atmospheric environment for their citizens.
  19. Ma TZ, Teh BT, Kho MY
    Sci Rep, 2024 Jul 16;14(1):16470.
    PMID: 39014100 DOI: 10.1038/s41598-024-67294-1
    Rapid urbanization will cause various land use changes and the vast occupation of green spaces, a critical factor in the deterioration of biodiversity in urbanized areas. Some species of wildlife are endangered due to habitat shrunk and fragmentation. However, Malaysia's current biodiversity protection range is still limited. The Ecological Network (EN) refers to a framework of ecological components, which can be obtained by geographical and technical approaches to support more ecological diversity ranges. Furthermore, little research has been found on EN in Malaysia and the impact of land use change on EN. Therefore, the Selangor region is selected as the study area. This paper quantifies land use change and measures the extent of land use change to obtain the EN's change. The result has shown that forestland has decreased, explored by people for housing and agriculture from 2000 to 2020. The EN has a trend of fragmentation. Overall, this study's results imply that the land use change led to EN's worsened performance from 2000 to 2020 in the study area. This paper hopes that this research could help supply information on conserving biodiversity in future development and urban sustainable planning in Malaysia.
    MeSH terms: Agriculture/methods; Conservation of Natural Resources*; Humans; Malaysia; Urbanization*; Ecosystem*; Biodiversity*; Forests
  20. A S, S S, J P, Prakash P, Sneha A
    Data Brief, 2024 Aug;55:110645.
    PMID: 39015255 DOI: 10.1016/j.dib.2024.110645
    Okra, renowned for its abundance of essential nutrients, emerges as a promising solution in addressing malnutrition, advocating for sustainable agriculture, and showcasing versatile untapped potentials. Our objective is to enhance the quality, market attractiveness, and culinary adaptability of okra harvests by classifying them into over-matured and adequately matured groups through a non-invasive approach. This dataset is centered on thermal images capturing different maturity levels of okra, categorized into two distinct groups. The thermal imaging device is employed for image capture, and the okra samples are sourced from diverse vegetable vendors and farms. This dataset proves to be a valuable asset for the non-invasive examination and categorization of okras based on their maturity levels.
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